Simulating the Effects of Land Surface Characteristics on Planetary Boundary Layer Parameters for a Modeled Landfalling Tropical Cyclone

This study examined whether varying moisture availability and roughness length for the land surface under a simulated Tropical Cyclone (TC) could affect its production of precipitation. The TC moved over the heterogeneous land surface of the southeastern U.S. in the control simulation, while the other simulations featured homogeneous land surfaces that were wet rough, wet smooth, dry rough, and dry smooth. Results suggest that the near-surface atmosphere was modified by the changes to the land surface, where the wet cases have higher latent and lower sensible heat flux values, and rough cases exhibit higher values of friction velocity. The analysis of areal-averaged rain rates and the area receiving low and high rain rates shows that simulations having a moist land surface produce higher rain rates and larger areas of low rain rates in the TC’s inner core. The dry and rough land surfaces produced a higher coverage of high rain rates in the outer regions. Key differences among the simulations happened as the TC core moved over land, while the outer rainbands produced more rain when moving over the coastline. These findings support the assertion that the modifications of the land surface can influence precipitation production within a landfalling TC.

A case study for cyclone ‘Aila’ for forecasting rainfall using satellite derived rain rate data

caxky dh [kkM+h esa cuus ,oa tehu ls Vdjkus okys pØokrh; rwQkuksa ds ifj.kkeLo:i Hkkjh o"kkZ dh otg ls if’pe caxky ds rV lesr Hkkjr ds iwohZ rV ds yksxksa dh tku eky dks dkQh [krjk jgrk gSA tehu ls Vdjkus okys m".kdfVca/kh; pØokrh rwQkuksa dh otg ls gksus okyh o"kkZ dh ek=k dk iwokZuqeku djuk cgqr dfBu gSA m".kdfVca/kh; pØokrh; rwQkuksa ds nk;js esa vkus okys o"kkZ okys {ks=ksa esa laHkkfor pØokrh; rwQku ls gksus okys o"kkZ lap;u dk iwokZuqeku djus ds fy, mixzg ls izkIr o"kkZ njksa dk mi;ksx fd;k tk ldrk gSA bl 'kks/k i= esa ‘vkbyk’ ds m".kdfVca/kh; o"kkZ ekiu fe’ku ¼Vh- vkj- ,e- ,e-½] mixzg o"kkZ nj vk¡dM+ksa rFkk rwQku ds ns[ks x, ekxZ dk mi;ksx djrs gq, m".kdfVca/kh; pØokr ‘vkbyk’ ds tehu ls Vdjkus ls 24 ?kVsa igys rVh; LVs’kuksa ij o"kkZ dk vkdyu djus dk iz;kl fd;k x;k gSA la;qDr jkT; vesfjdk esa fodflr lqifjfpr rduhd ds vk/kkj ij m".kdfVca/kh; pØokr ‘vkbyk’ ds tehu ls Vdjkus ds 24 ?kaVs igys m".kdfVca/kh; o"kkZ foHko ¼Vh- vkj- ,- ih-½ iwokZuqeku fo’ks"k :i ls rwQku dh fn’kk ds lkeus vkus okys rVh; {ks=ksa ds fy, vPNh o"kkZ dk iwokZuqeku miyC/k djkrk gSA Major threat to the life and property of people on the east coast of India, including West Bengal Coast, is due to very heavy rainfall from landfalling tropical cyclones originated over Bay of Bengal. Forecasting magnitude of rainfall from landfalling tropical cyclones is very difficult. Satellite derived rain rates over the raining areas of tropical cyclones can be used to forecast potential tropical cyclone rainfall accumulations. In the present study, an attempt has been made to estimate 24 hours rainfall over coastal stations before landfall of tropical Cyclone ‘Aila’ using Tropical Rainfall Measuring Mission (TRMM) satellite rain rates data and observed storm track of Aila. Forecast Tropical Rainfall Potential (TRaP), 24 hours prior to landfall for the tropical cyclone ‘Aila’ based on well known technique developed in USA, provides a good rainfall forecast especially for the coastal areas lying at the head of direction of the storm.

Characterisation and asymmetry analysis of rainfall distribution associated with tropical cyclones over Bay of Bengal : NISHA (2008), LAILA (2010) and JAL (2010)

The precipitation characteristics and spatial rainfall asymmetry in respect of three tropical cyclones (TCs) of Bay of Bengal, viz., NISHA (2008), LAILA (2010) and JAL(2010) that affected coastal Tamil Nadu are studied using TRMM based rain rate data. The analysis is carried out by dividing the life cycle of the TC into various stages of intensification and weakening. Percentage frequency distribution, radial profile and quadrant-wise mean rain rates are determined stage-wise for each TC. Further, spatio-temporal variations in the rainfall asymmetry is studied using Fourier analysis by computing the first order wave number-1 asymmetry around the TC centre. The results indicate a shifting of higher frequency rain rates from higher to lower rain rate side when the TC passes from intensification to weakening stages. The azimuthally averaged mean rain rates indicate a peak rain rate of 4-5 mm/hr over 50-100 km from the TC centre during intensification stages which decreases to a very low rate of about 1 mm/hr during the final stages of weakening. For the same intensity category, the radial profiles of mean rain rates show marked difference between the intensification and weakening stages. The quadrant mean rain rates show large asymmetries in the radial rainfall distribution with more rainfall concentrated in front left quadrant during the stages of intensification. Such TC rainfall asymmetries are shown to be influenced by the environmental vertical wind shear and translational speed of the TC. When the wind shear and storm motion vectors are in the same direction, a dominant down shear left asymmetry is observed. Evolution of wave number-1 asymmetry indicates that, by and large, asymmetry amplitude increases from the centre outwards and a cyclonic (anti-cyclonic) shift during the intensification (weakening) stages of the TCs.

Idealized simulation study of the relationship of disdrometer sampling statistics with the precision of precipitation rate measurement

Due to the discretized nature of rain, the measurement of a continuous precipitation rate by disdrometers is subject to statistical sampling errors. Here, Monte Carlo simulations are employed to obtain the precision of rain detection and rate as a function of disdrometer collection area and compared with World Meteorological Organization guidelines for a 1 min sample interval and 95 % probability. To meet these requirements, simulations suggest that measurements of light rain with rain rates R ≤ 0.50 mm h−1 require a collection area of at least 6 cm × 6 cm, and for R = 1 mm h−1, the minimum collection area is 13 cm × 13 cm. For R = 0.01 mm h−1, a collection area of 2 cm × 2 cm is sufficient to detect a single drop. Simulations are compared with field measurements using a new hotplate device, the Differential Emissivity Imaging Disdrometer. The field results suggest an even larger plate may be required to meet the stated accuracy, likely in part due to non-Poissonian hydrometeor clustering.

Linkages of Active and Weakening MJO events to Seasonal Variations over the Maritime Continent

The Madden-Julian Oscillation (MJO) is a large-scale phenomenon of air-sea intra-seasonal variability in the equatorial area, particularly in the Maritime Continent (MC). This research focused on the analysis of the MJO propagation process in association with rainfall events and sea surface temperature anomaly (SSTA) during seasonal variations, i.e., November, December, January February, and March (NDJFM), and May, June, July, August September (MJJAS). MJO events from 2010 to 2019 were classified as MJO active or MJO weakening according to propagation characteristics and amplitude changes in the RMM index. This research uses a dataset of 10-year series of daily Tropical Rainfall Measuring Mission (TRMM) (3B42 V7 derived) measurements for detecting rain rates. Daily OLR data from the NOAA Physical Sciences Laboratory and SSTA daily data from Physical Oceanography Distributed Active Archive Centre (PODAAC) NOAA are considered for analysing MJO propagation. Composites of outgoing longwave radiation (OLR) were also identified differences between the two events; active MJO events had consistently higher negative OLR anomalies than weakening MJO events. Active MJO events during NDJFM had a higher rain rate and positive SSTA than weakening MJO events. Furthermore, composite rain rates distribution over MC during NDJFM are mainly located in the south of the equator, contrarily when MJJAS are north of the equator.

Validation of Three Daily Satellite Rainfall Products in a Humid Tropic Watershed, Brantas, Indonesia: Implications to Land Characteristics and Hydrological Modelling

A total of three different satellite products, CHIRPS, GPM, and PERSIANN, with different spatial resolutions, were examined for their ability to estimate rainfall data at a pixel level, using 30-year-long observations from six locations. Quantitative and qualitative accuracy indicators, as well as R2 and NSE from hydrological estimates, were used as the performance measures. The results show that all of the satellite estimates are unsatisfactory, giving the NRMSE ranging from 6 to 30% at a daily level, with CC only 0.21–0.36. Limited number of gauges, coarse spatial data resolution, and physical terrain complexity were found to be linked with low accuracy. Accuracy was slightly better in dry seasons or low rain rate classes. The errors increased exponentially with the increase in rain rates. CHIPRS and PERSIANN tend to slightly underestimate at lower rain rates, but do show a consistently better performance, with an NRMSE of 6–12%. CHRIPS and PERSIANN also exhibit better estimates of monthly flow data and water balance components, namely runoff, groundwater, and water yield. GPM has a better ability for rainfall event detections, especially during high rainfall events or extremes (>40 mm/day). The errors of the satellite products are generally linked to slope, wind, elevation, and evapotranspiration. Hydrologic simulations using SWAT modelling and the three satellite rainfall products show that CHIRPS slightly has the daily best performance, with R2 of 0.59 and 0.62, and NSE = 0.54, and the monthly aggregated improved at a monthly level. The water balance components generated at an annual level, using three satellite products, show that CHIRPS outperformed with a ration closer to one, though with a tendency to overestimate up to 3–4× times the data generated from the rainfall gauges. The findings of this study are beneficial in supporting efforts for improving satellite rainfall products and water resource implications.

Growth of Mesoscale Convective Systems in Observations and a Seasonal Convection-Permitting Simulation over Argentina

A 6.5-month, convection-permitting simulation is conducted over Argentina covering the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations and Clouds, Aerosols, and Complex Terrain Interactions (RELAMPAGO-CACTI) field campaign and is compared with observations to evaluate mesoscale convective system (MCS) growth prediction. Observed and simulated MCSs are consistently identified, tracked, and separated into growth, mature, and decay stages using top-of-the-atmosphere infrared brightness temperature and surface rainfall. Simulated MCS number, lifetime, seasonal and diurnal cycles, and various cloud-shield characteristics including growth rate are similar to those observed. However, the simulation produces smaller rainfall areas, greater proportions of heavy rainfall, and faster system propagations. Rainfall area is significantly underestimated for long-lived MCSs but not for shorter-lived MCSs, and rain rates are always overestimated. These differences result from a combination of model and satellite retrieval biases, in which simulated MCS rain rates are shifted from light to heavy, while satellite-retrieved rainfall is too frequent relative to rain gauge estimates. However, the simulation reproduces satellite-retrieved MCS cloud-shield evolution well, supporting its usage to examine environmental controls on MCS growth. MCS initiation locations are associated with removal of convective inhibition more than maximized low-level moisture convergence or instability. Rapid growth is associated with a stronger upper-level jet (ULJ) and a deeper northwestern Argentinean low that causes a stronger northerly low-level jet (LLJ), increasing heat and moisture fluxes, low-level vertical wind shear, baroclinicity, and instability. Sustained growth corresponds to similar LLJ, baroclinicity, and instability conditions but is less sensitive to the ULJ, large-scale vertical motion, or low-level shear. Growth sustenance controls MCS maximum extent more than growth rate.

Skilful precipitation nowcasting using deep generative models of radar

Precipitation nowcasting, the high-resolution forecasting of precipitation up to two hours ahead, supports the real-world socioeconomic needs of many sectors reliant on weather-dependent decision-making1,2. State-of-the-art operational nowcasting methods typically advect precipitation fields with radar-based wind estimates, and struggle to capture important non-linear events such as convective initiations3,4. Recently introduced deep learning methods use radar to directly predict future rain rates, free of physical constraints5,6. While they accurately predict low-intensity rainfall, their operational utility is limited because their lack of constraints produces blurry nowcasts at longer lead times, yielding poor performance on rarer medium-to-heavy rain events. Here we present a deep generative model for the probabilistic nowcasting of precipitation from radar that addresses these challenges. Using statistical, economic and cognitive measures, we show that our method provides improved forecast quality, forecast consistency and forecast value. Our model produces realistic and spatiotemporally consistent predictions over regions up to 1,536 km × 1,280 km and with lead times from 5–90 min ahead. Using a systematic evaluation by more than 50 expert meteorologists, we show that our generative model ranked first for its accuracy and usefulness in 89% of cases against two competitive methods. When verified quantitatively, these nowcasts are skillful without resorting to blurring. We show that generative nowcasting can provide probabilistic predictions that improve forecast value and support operational utility, and at resolutions and lead times where alternative methods struggle.

Turbulence in The Marine Boundary Layer and Air Motions Below Stratocumulus Clouds at the ARM Eastern North Atlantic Site

Marine stratocumulus clouds are intimately coupled to the turbulence in the boundary layer and drizzle is known to be ubiquitous within them. Six years of data collected at the Atmospheric Radiation Measurement (ARM)’s Eastern North Atlantic site are utilized to characterize turbulence in the marine boundary layer and air motions below stratocumulus clouds. Profiles of variance of vertical velocity binned by wind direction (wdir) yielded that the boundary layer measurements are affected by the island when the wdir is between 90° and 310° (measured clockwise from North where air is coming from). Data collected during the marine conditions (wdir<90 or wdir>310) showed that the variance of vertical velocity was higher during the winter months than during the summer months due to higher cloudiness, wind speeds, and surface fluxes. During marine conditions the variance of vertical velocity and cloud fraction exhibited a distinct diurnal cycle with higher values during the nighttime than during the daytime. Detailed analysis of 32 cases of drizzling marine stratocumulus clouds showed that for a similar amount of radiative cooling at the cloud top, within the sub-cloud layer 1) drizzle increasingly falls within downdrafts with increasing rain rates, 2) the strength of the downdrafts increases with increasing rain rates, and 3) the correlation between vertical air motion and rain rate is highest in the middle of the sub-cloud layer. The results presented herein have implications for climatological and model evaluation studies conducted at the ENA site, along with efforts of accurately representing drizzle-turbulence interactions in a range of atmospheric models.

Performance of the DBS Satellite Receiver under the Impact of Rainfall and Terrestrial Interference

This article presents a new study on the feasibility of operating a direct broadcasting satellite (DBS) system under the effect of both precipitation and interference from a fixed service (FS) at K-band in a semiarid region. The carrier-to-noise plus interference ratio (CNIR) as a protection criterion has been adopted to make sure that the receiver of the DBS system operates with an acceptable performance under rainfall and interference from FS. Various measured data for rainfall in different areas have been utilized to investigate different rain rate exceedance percentages. Results have been shown that areas with high rain rates have a small CNIR at the DBS receiver and require large protection distances compared to low-rain rate areas and vice versa. Some mitigation techniques have been suggested to alleviate the effect of rain and terrestrial interference on the DBS receiver performance.